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Cyberinfrastructure Framework for 21st Century Science & Engineering (CIF21) NSF-wide Cyberinfrastructure Vision People, Sustainability, Innovation, Integration Alan Blatecky Acting Director OCI. 1. Framing the Challenge: Science and Society Transformed by Data. Modern science

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slide1

Cyberinfrastructure Frameworkfor 21st Century Science & Engineering (CIF21)

NSF-wide Cyberinfrastructure Vision

People, Sustainability, Innovation, Integration

Alan Blatecky

Acting Director OCI

1

framing the challenge science and society transformed by data
Framing the Challenge:Science and Society Transformed by Data
  • Modern science
    • Data- and compute-intensive
    • Integrative, multiscale
  • Multi-disciplinary Collaborations for Complexity
    • Individuals, groups, teams, communities
  • Sea of Data
    • Age of Observation
    • Distributed, central repositories, sensor- driven, diverse, etc
acci task force reports
ACCI Task Force Reports
  • Final recommendations presented to the NSF Advisory Committee on Cyberinfrastructure Dec 2010
  • More than 25 workshops and Birds of a Feather sessions and more than 1300 people involved
    • Final reports on-line

Campus

Bridging

Data and Viz

HPC

HIGH P ERFORMANCE COMPUTING

Grand

Challenges

Cyberlearning

Software

recommendation of nsf advisory committee on cyberinfrastructure acci
Recommendation of NSF Advisory Committee on CyberinfrastructureACCI

"The National Science Foundation should create a program in Computational and Data-Enabled Science and Engineering (CDS&E), based in and coordinated by the NSF Office of Cyberinfrastructure. The new program should be collaborative with relevant disciplinary programs in other NSF directorates and offices."

grand challenges task force recommendations oden
Grand Challenges Task Force Recommendations (Oden)
  • Permanent, integrative activities in CDS&E are critically needed at NSF to address current and emerging Grand Challenge Problems
  • An interagency group in CDS&E should be established to address national goals and priorities and to ensure coordination of efforts
  • Support of diverse HPC activities (hardware, methods, algorithms) should remain a high priority. University researchers need open access to these resources at all levels
  • The development of robust, reliable and useable software at all levels needs to supported by NSF and recognized as an important component of the research portfolio of NSF
  • Support CI for data and visualization
  • Learn how to create grand challenge communities and VOs (and do it!)
campus bridging recommendations stewart
Campus Bridging Recommendations (Stewart)
  • NSF should
    • Study successful campus CI implementations to document and disseminate the best practices for strategies, governance, financial models and deployment
    • Establish a blueprint and roadmap for national CI, including
      • Standard Authentication (InCommon)
      • MRI awards at campus level
      • National Data infrastructure, including national networking backbone
  • Campuses should
    • Develop a Cyberinfrastructure master plan with the goal of identifying and planning for the changing research infrastructure needs of faculty and researchers
    • Work toward a goal of providing their educators and researchers access to a seamless Cyberinfrastructure which supports and accelerates research and education
software task force recommendations keyes
Software Task Force Recommendations (Keyes)
  • Develop a multi-level (individual, team, institute), long-term program to support scientific software
  • Promote verification, validation, sustainability, and reproducibility through software developed with federal support
  • Develop a uniform policy on open source that promotes scientific discovery and encourages innovation
  • Support software through collaborations among all of its divisions, related federal agencies, and private industry
  • Utilize its Advisory Committees (including Directorate level) to obtain community input on software priorities
data task force recommendations baker hey
Data Task Force Recommendations (Baker, Hey)
  • Infrastructure: NSF should recognize data infrastructure and services (including visualization) as essential research assets fundamental to today’s science and as long-term investments in national prosperity
  • Culture Change: NSF should reinforce expectations for data sharing; support the establishment of new citation models in which data and software tool providers and developers are credited with their contributions
  • Economic sustainability: NSF should develop and publish realistic cost models to underpin institutional/national business plans for research repositories/data services
  • Data Management Guidelines: NSF should identify and share best-practices for the critical areas of data management
  • Ethics and IP: NSF should train researchers in privacy-preserving data access
hpc task force recommendations zacharia
HPC Task Force Recommendations (Zacharia)
  • Develop a sustainable model to provide the academic research community with access to a rich mix of HPC systems
    • 20-100 PF, integrated nationally, supported at campus levels
    • Invest now for exascale systems by 2018-2020
  • Continue and grow a variety of education, outreach, and training programs to expand awareness and encourage the use of high-end modeling and simulation
  • Broaden outreach to improve the preparation of researchers and to engage industry, decision-makers, and new user communities in the use of HPC as a valuable tool
  • Provide funding for digital data framework to address the issues of knowledge discovery including co-location of archives and data resources with compute and visualization resources as appropriate.
cyberlearning and workforce development task force recommendations ramirez
Cyberlearning and Workforce Development Task Force Recommendations (Ramirez)
  • Overall: Continuous, Collaborative, Computation Cloud (C4)
    • Pervasive/ubiquitous Internet-based, interacting devices, data sources, users to dominate research, education & all areas of human endeavor
  • Promote cross-disciplinary, transformative research and education
    • Systemic change needed at all levels of education; university structures adjusted to train next generation scientists
  • Invest in efforts to understand learning and research mechanisms and organizations in the new world of CI
    • Exploit and transform CI-enabled, STEM research advancements, tools, and resources for cyberlearning and workforce development purposes
  • Focus on lifelong learning and professional development
  • Strengthen leadership, fund research in broadening participation: elimination of underrepresentation of women, persons with disabilities, and minorities
slide11

Cyberinfrastructure Ecosystem (CIF21)

Organizations

Universities, schools

Government labs, agencies

Research and Medical Centers

Libraries, Museums

Virtual Organizations

Communities

Scientific Instruments

Large Facilities, MREFCs,,telescopes

Colliders, shake Tables

Sensor Arrays

- Ocean, environment, weather,

buildings, climate. etc

Expertise

Research and Scholarship

Education

Learning and Workforce Development

Interoperability and operations

Cyberscience

Discovery

Collaboration

Education

Data

Databases, Data repositories

Collections and Libraries

Data Access; storage, navigation

management, mining tools,

curation, privacy

Computational Resources

Supercomputers

Clouds, Grids, Clusters

Visualization

Compute services

Data Centers

Networking

Campus, national, international networks

Research and experimental networks

End-to-end throughput

Cybersecurity

Software

Applications, middleware

Software development and support

Cybersecurity: access,

authorization, authentication

Maintainability, sustainability, and extensibility

cif21 a metaphor
CIF21 – a metaphor
  • A goal of Virtual Proximity –-- “ you are one with your resources”
    • Continue to collapse the barrier of distance and remove geographic location as an issue
    • ALL resources (including people) are virtually present, accessible and secure
    • End-to-end integrated resources
    • Science, discovery, innovation, education are the metrics

An organizing fabric and foundation for science, engineering and education

broad principles to lead cif21
Broad Principles to Lead CIF21
  • Builds national infrastructure for S&E
  • Leverages common methods, approaches, and applications – focus on interoperability
  • Catalyzes other CI investments across NSF
    • Provides focus and is a vehicle for coordinating efforts and programs
    • Is a “force multiplier” across NSF
  • Shared governance; embedded into every directorate and office
  • Managed as a coherent program
slide14

Four Thrust Areas

Organizations

Universities, schools

Government labs, agencies

Research and Medical Centers

Libraries, Museums

Virtual Organizations

Communities

Community

Research

Networks

Scientific Instruments

Large Facilities, MREFCs,,telescopes

Colliders, shake Tables

Sensor Arrays

- Ocean, environment, weather,

buildings, climate. etc

Expertise

Research and Scholarship

Education

Learning and Workforce Development

Interoperability and operations

Cyberscience

Data-Enabled Science

Discovery

Collaboration

Education

Education: integral and embedded

Data

Databases, Data repositories

Collections and Libraries

Data Access; storage, navigation

management, mining tools,

curation, privacy

Computational Resources

Supercomputers

Clouds, Grids, Clusters

Visualization

Compute services

Data Centers

New Computational

Resources

Access and

Connections to

CI Resources

Networking

Campus, national, international networks

Research and experimental networks

End-to-end throughput

Cybersecurity

Software

Applications, middleware

Software development and support

Cybersecurity: access,

authorization, authentication

data enabled science thrust area 1
Data-Enabled ScienceThrust Area 1
  • Data Services Program (data)
    • Provide reliable digital preservation, access, integration, and analysis capabilities for science and/or engineering data over a decades-long timeline
  • Data Analysis and Tools Program (information)
    • Data mining, manipulation, modeling, visualization, decision-making systems
  • Data-intensive Science Program (knowledge)
    • Intensive disciplinary efforts,

multi-disciplinary discovery

and innovation

Dumped On by Data: Scientists Say a Deluge Is Drowning Research

data challenges
Data Challenges

Square

Kilometer

Array

Climate,

Environment

Exa

Bytes

Peta

Bytes

Tera

Bytes

Giga

Bytes

Volume of data

Genomics

Climate,

Environment

Blue

Waters

LHC

Growth

LSST

LHC

Genomics

Distribution of data

2012 2016 2020

Interoperability of Data

public data being created
Public Data Being Created

Zetta Bytes

Exa

Bytes

Peta

Bytes

Tera

Bytes

Sciencexpress

Square

Kilometer

Array

Climate,

Environment

IDC

Genomics

Climate,

Environment

Blue

Waters

LHC

LSST

LHC

Genomics

2012 2016 2020

new computational infrastructure thrust area 2
New Computational InfrastructureThrust Area 2
  • Computational and Data-enabled resources
    • HPC, Clouds, Clusters, Data Centers
  • Long-term software for science and engineering
    • Sustained software development and support
  • Discipline-specific activities
    • Services, tools, compute environments that serve specific research efforts and communities
creating scalable software development environments
Creating Scalable SoftwareDevelopment Environments
  • Create a software ecosystem that scales from individual or small groups of software innovators to large hubs of software excellence

Focus on innovation Focus on sustainability

community research networks thrust area 3
Community Research NetworksThrust Area 3
  • New multidisciplinary research communities
    • Address challenges beyond individuals and disciplinary research communities
    • Support and optimize collaboration across small, mid-level and large community networks
    • Support SEES and new research communities
  • Advanced research on community and social networks
    • Structures, leadership, fostering and sustainability
    • “virtuous cycle” providing feedback through formal evaluation and program iteration
access and connectivity thrust area 4
Access and Connectivity Thrust Area 4
  • Network connections and engineering program
    • Real-time access to facilities and instruments; Begins to tie in MREFC activities
    • Integration and end-to-end performance to provide seamless access from researcher to resource
  • Cybersecurity – from innovation to practice
    • Deployment of identity management systems
    • Development of cybersecurity prototypes
cif21 strategic plan
CIF21 Strategic Plan
  • Development of a detailed CIF21 Roadmap for FY12 and beyond; updated as needed
  • Developing a plan and guide for CI investments across NSF
  • Established internal NSF working group
  • Exploring and developing data policies on open access, publications, citation, etc
  • Multidirectorate/office “collective” programs designed to build critical infrastructure and capabilities
cif21 strategy plan con t
CIF21 Strategy Plan con’t
  • Outcomes and metrics being identified for each Thrust Area
  • Spiral development model adopted for all components
    • 3-5 year overlapping spirals
    • Iteration and creation of new versions and capabilities with each spiral
    • Ever increasing improvements
  • NSF Advisory Committee on Cyberinfrastructure to review CIF21 progress; individual directorate ACs as well
transient data intensive astronomy
Transient & Data-intensive Astronomy
  • New era: seeing events as they occur
    • (Almost) here now
      • ALMA, EVLA in radio
      • Ice Cube neutrinos
    • On horizon
      • 24-42m optical?
      • LIGO south?
      • LSST = SDSS (40TB) every night!
      • SKA = exabytes
  • Simulations integrate all physics

?

earth systems and cif21
Earth Systems and CIF21

A Complex Interconnected Earth System

slide26

Earth–Human Knowledge Management System (Earth-Cubed)

for

Discovery Observing Simulating

Sharing Collaborating Training

 Learning  Informing Broadening Participation

impacts on nsf
Impacts on NSF
  • CI as enabling infrastructure for S&E
    • Sustainability and viability essential
    • NSF has a unique role in this strategy
  • New role for Data
    • data-enabled and data intensive science
    • management of data - compute, storage, use, access, etc
  • Multi-disciplinary approaches essential
  • Education - embedded and integral
    • methodologies (compute and data intensive)
    • culture/society (interdisciplinary approaches, collaborative)
  • More coordinated post-award management
    • ensure value across the entire research enterprise